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20182022
most citedAlleviating the Sample Selection Bias in Few-shot Learning by Removing Projection to the Centroid

8 citations · 10 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV20228 cited

Alleviating the Sample Selection Bias in Few-shot Learning by Removing Projection to the Centroid

Jing Xu, Xu Luo, Xinglin Pan +3

Few-shot learning (FSL) targets at generalization of vision models towards unseen tasks without sufficient annotations. Despite the emergence of a number of few-shot learning metho…

cs.CV2021

AFINet: Attentive Feature Integration Networks for Image Classification

Xinglin Pan, Jing Xu, Yu Pan +4

Convolutional Neural Networks (CNNs) have achieved tremendous success in a number of learning tasks including image classification. Recent advanced models in CNNs, such as ResNets,…

eess.IV20212 cited

RegNet: Self-Regulated Network for Image Classification

Jing Xu, Yu Pan, Xinglin Pan +3

The ResNet and its variants have achieved remarkable successes in various computer vision tasks. Despite its success in making gradient flow through building blocks, the simple sho…

cs.CV2021

MultiFace: A Generic Training Mechanism for Boosting Face Recognition Performance

Jing Xu, Tszhang Guo, Yong Xu +2

Deep Convolutional Neural Networks (DCNNs) and their variants have been widely used in large scale face recognition(FR) recently. Existing methods have achieved good performance on…

cs.CV2018

Compressing Recurrent Neural Networks with Tensor Ring for Action Recognition

Yu Pan, Jing Xu, Maolin Wang +4

Recurrent Neural Networks (RNNs) and their variants, such as Long-Short Term Memory (LSTM) networks, and Gated Recurrent Unit (GRU) networks, have achieved promising performance in…